Background: A real-time peptide-spectrum matching (RT-PSM) algorithm is a database search method to interpret tandem mass spectra (MS/MS) with strict time constraints. Restricted by the hardware and architecture of individual workstation, previous RT-PSM algorithms either are not fast enough to satisfy all real-time system requirements or need to sacrifice the level of inference accuracy to provide the required processing speed. Results: We develop two parallelized algorithms for MS/MS data analysis: a multi-core RT-PSM (MC RT-PSM) algorithm which works on individual workstations and a distributed computing RT-PSM (DC RT-PSM) algorithm which works on a computer cluster. Two data sets are employed to evaulate the performance of our proposed algorithms. The simulation results show that our proposed algorithms can reach approximately 216.9-fold speedup on a sub-task process (similarity scoring module) and 84.78-fold speedup on the overall process compared with a single-thread process of the RT-PSM algorithm when 240 logical cores are employed. Conclusions: The improved RT-PSM algorithms can achieve the processing speed requirement without sacrificing the level of inference accuracy. With some configuration adjustments, the proposed algorithm can support many peptide identification programs, such as X!Tandem, CUDA version RT-PSM, etc.